GPT-4.1 Nano vs GPT-5.4 Nano
Benchmark Performance
Available Benchmarks
| Benchmark | GPT-4.1 Nano | GPT-5.4 Nano |
|---|---|---|
| LMArena Text Arenatext-2026-09-01-011508720696 · arena_rating · leader | 1,284.6494% of row best · rating · gpt-4.1-nano-2025-04-14; 95% CI [1276.99177350, 1292.27849322]; votes 6103; rank 246 | 1,372.87100% of row best · rating · gpt-5.4-nano-high; 95% CI [1369.01004978, 1376.72255426]; votes 58562; rank 163 |
| LMArena Vision Arenavision-2026-08-27-011508720696 · arena_rating · leader | 1,063.2389% of row best · rating · gpt-4.1-nano-2025-04-14; 95% CI [1044.95116252, 1081.50991534]; votes 1211; rank 120 | 1,197.82100% of row best · rating · gpt-5.4-nano-high; 95% CI [1191.24291416, 1204.39749063]; votes 23952; rank 76 |
| Overall ResultCounted from the protocol-matched rows above | 0 benchmark wins | 2 benchmark winsOverall lead |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Technical Differences
Side-by-Side Facts
| Field | GPT-4.1 Nano | GPT-5.4 Nano |
|---|---|---|
| Developer | Openai | Openai |
| Family | Gpt 4 1 | Gpt 5 4 |
| Model | GPT-4.1 Nano | GPT-5.4 Nano |
| Version | GPT-4.1 Nano | GPT-5.4 Nano |
| Lifecycle | active | active |
| Released | Unknown | 2026-03-17 |
| Knowledge cutoff | 2024-06-01 | 2025-08-31 |
| Input modalities | Unknown | Unknown |
| Output modalities | Unknown | Unknown |
| Context window | 1,047,576 | 400,000 |
| Total parameters | Unknown | Unknown |
| Active parameters | Unknown | Unknown |
| License | Unknown | Unknown |
| Open weights | No | No |
| API available | Yes | Yes |
| Self-hostable | No | No |
| Provider access | Openai (Standard), Openrouter (Standard) | Openai (Standard), Openrouter (Standard) |
| Capabilities | chat, generation, tools | chat, generation, reasoning, structured_outputs, tools |
12 comparable fields · 6 material differences · Interactive comparison only; indexing gate not met
GPT-4.1 Nano Capabilities
GPT-5.4 Nano Capabilities
Primary Evidence
Sources and Freshness
Questions
GPT-4.1 Nano vs GPT-5.4 Nano FAQs
Is GPT-4.1 Nano or GPT-5.4 Nano better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both GPT-4.1 Nano and GPT-5.4 Nano, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, GPT-4.1 Nano or GPT-5.4 Nano?+
GPT-4.1 Nano is $0.050 and GPT-5.4 Nano is $0.20 per million tokens, so GPT-4.1 Nano is cheaper on this metric. GPT-4.1 Nano is $0.20 and GPT-5.4 Nano is $1.25 per million tokens, so GPT-4.1 Nano is cheaper on this metric.
Which has a larger context window, GPT-4.1 Nano or GPT-5.4 Nano?+
GPT-4.1 Nano has the larger sourced context window. GPT-4.1 Nano supports 1,047,576 and GPT-5.4 Nano supports 400,000.
Which performs better in benchmarks, GPT-4.1 Nano or GPT-5.4 Nano?+
There is no overall benchmark winner: An overall winner requires at least two decisive benchmarks from at least two original publishers.
Can GPT-4.1 Nano or GPT-5.4 Nano be self-hosted?+
Both models have the same recorded self-hosting status: unsupported. GPT-4.1 Nano is not marked open weight; GPT-5.4 Nano is not marked open weight.
Can GPT-4.1 Nano and GPT-5.4 Nano understand images?+
GPT-4.1 Nano is not documented with image input; GPT-5.4 Nano is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, GPT-4.1 Nano or GPT-5.4 Nano?+
GPT-5.4 Nano has the larger sourced maximum output: GPT-4.1 Nano supports 32,768 and GPT-5.4 Nano supports 128,000 output tokens.
Do GPT-4.1 Nano and GPT-5.4 Nano support reasoning and tool use?+
GPT-4.1 Nano: tool calling. GPT-5.4 Nano: reasoning and tool calling. Feature support does not establish relative quality.
Which is available from more inference providers, GPT-4.1 Nano or GPT-5.4 Nano?+
GPT-4.1 Nano has 2 sourced provider routes; GPT-5.4 Nano has 2, a tie.
Which offers better value, GPT-4.1 Nano or GPT-5.4 Nano?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.